A C++ library for Bayesian modeling, mainly through Markov chain Monte Carlo, but with a few other methods supported. BOOM = "Bayesian Object Oriented Modeling". It is also the sound your computer makes when it crashes.
GNU Lesser General Public License v2.1
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Handle zero-variance state components in a better way. #54
The current bsts model assumes that the state has variance R Q R', where R is rectangular block diagonal and Q is block diagonal. For state models (blocks) that have zero variance, we should skip a block in Q, and instead of having a separate block for R, the R for the previous model should have a row of 0's appended.
This will required reconfiguring the StateModelVector, but shouldn't be too hard.
The motivating model here is the Seasonal model with season.duration > 0.
The current bsts model assumes that the state has variance R Q R', where R is rectangular block diagonal and Q is block diagonal. For state models (blocks) that have zero variance, we should skip a block in Q, and instead of having a separate block for R, the R for the previous model should have a row of 0's appended.
This will required reconfiguring the StateModelVector, but shouldn't be too hard.
The motivating model here is the Seasonal model with season.duration > 0.